code: def step(self, state, x=None, y=None):
      v = pyro.sample("v_{}".format(self.t), dist.Normal(0.0, 1.0))
      with pyro.plate("plate", self.plate_size):
          w = pyro.sample("w_{}".format(self.t), dist.Normal(v, 1.0))
          x = pyro.sample(
              "x_{}".format(self.t),
              dist.Normal(state["x_mean"] + w, 1),
              obs=x,
          )
          y = pyro.sample(
              "y_{}".format(self.t),
              dist.MultivariateNormal(
                  state["y_mean"] + w.unsqueeze(-1),
                  torch.eye(self.state_size),
              ),
              obs=y,
          )
      self.t += 1
      return x, y
  
imports: import pytest
  import torch
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.infer import SMCFilter
  from pyro.infer.smcfilter import _systematic_sample
  from tests.common import assert_close
label_desc: Use image node_id 3 for calling the SmokeModel obj's underlying member method code with example usage: obj.step(state, x, y) and returns: x,  y